Depending on the context of your search, the "juq016 2021 link" keyword generally aligns with one of three primary digital asset categories: 1. Academic and Scientific Research Papers
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– JUQ016 includes a subset of 100 “hardware‑friendly” molecules whose minimal basis‑set Hamiltonians can be encoded in ≤ 30 qubits. The authors provide ready‑to‑run Qiskit and Cirq circuits, along with reference results obtained on IBM Quantum Falcon and Rigetti Aspen platforms.
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Below is a concise Python snippet (using the juq-data helper library) that demonstrates how to fetch the first 10 molecules, read their geometries, and compute the mean absolute error (MAE) of a user‑provided density functional against the reference CCSD(T) energies. Depending on the context of your search, the
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# 2. Extract reference energies (CCSD(T)) and geometries ref_energies = np.array([e['ccsd_t_energy'] for e in entries]) geometries = [e['geometry'] for e in entries]
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